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» Scalable inference in latent variable models
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133
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ACL
2007
15 years 5 months ago
Constituent Parsing with Incremental Sigmoid Belief Networks
We introduce a framework for syntactic parsing with latent variables based on a form of dynamic Sigmoid Belief Networks called Incremental Sigmoid Belief Networks. We demonstrate ...
Ivan Titov, James Henderson
CVPR
2010
IEEE
15 years 9 months ago
Many-to-one Contour Matching for Describing and Discriminating Object Shape
We present an object recognition system that locates an object, identifies its parts, and segments out its contours. A key distinction of our approach is that we use long, salien...
Praveen Srinivasan, Qihui Zhu, Jianbo Shi
136
Voted
TIP
2008
133views more  TIP 2008»
15 years 4 months ago
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
Jason K. Johnson, Alan S. Willsky
ICASSP
2010
IEEE
15 years 4 months ago
Supervised topic model for automatic image annotation
This paper presents a new probabilistic model for the task of image annotation. Our model, which we call sLDA-bin, extends supervised Latent Dirichlet Allocation (sLDA) model to h...
Duangmanee Putthividhya, Hagai Thomas Attias, Srik...
ICA
2007
Springer
15 years 8 months ago
Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
Ali Taylan Cemgil, Onur Dikmen